Groundwater is a crucial resource across agricultural, civil, and industrial sectors. The
prediction of groundwater pollution due to various chemical components is vital for planning …

The rapid development to accommodate population growth has a detrimental effect on water
quality, which is deteriorating. Consequently, water quality prediction has emerged as a …

Groundwater vulnerability and pollution hazard in the Braga shallow aquifer were assessed
through an integrated GIS-based multicriteria analysis and Artificial Neural Network (ANN) …

Groundwater quality for irrigation purposes varies across regions, countries, and specific
locations, primarily due to factors such as groundwater extraction and utilization methods …

The present study has applied artificial neural network (ANN) and multiple linear regression
(MLR) techniques to predict the fitness of groundwater quality for drinking from Shivganga …

Present research work emphasizes the integrated approach of heavy metal pollution indices
coupled with multivariate statistical analysis to evaluate the health risk from groundwater of …

Abstract Machine learning algorithms have proven useful in the estimation, classification,
and prediction of water quality parameters. Similarly, indexical modeling has enhanced the …

Groundwater quality monitoring in the vicinity of drilling sites is crucial for the protection of
water resources. Selected physicochemical parameters of waters were marked in the study …

The continuous increase in the rate of industrialization in developing countries, in recent
times, calls for continuous industrial water quality assessment and prediction. This is to …

The prediction accuracies of machine learning (ML) models may not only be dependent on
the input parameters and training dataset, but also on whether an ensemble or individual …